Addressing GPU On-Chip Shared Memory Bank Conflicts Using Elastic Pipeline


One of the major problems with the GPU on-chip shared memory is bank conflicts. We analyze that the throughput of the GPU processor core is often constrained neither by the shared memory bandwidth, nor by the shared memory latency (as long as it stays constant), but is rather due to the varied latencies caused by memory bank conflicts. This results in… (More)
DOI: 10.1007/s10766-012-0201-1


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@article{Gou2012AddressingGO, title={Addressing GPU On-Chip Shared Memory Bank Conflicts Using Elastic Pipeline}, author={Chunyang Gou and Georgi Gaydadjiev}, journal={International Journal of Parallel Programming}, year={2012}, volume={41}, pages={400-429} }